- Product delivery leadership
- Own the roadmap for AIenabled onboarding intake recommendation approvals provisioning audit evidence
- Translate onboarding pain points into prioritised use cases user stories and measurable outcomes
- Run delivery cadence across IAM ops engineering and data science teams
- manage RAID and dependencies
- AIenabled onboarding capabilities
- Deliver capabilities such as Accessrole recommendations based on joiner attributes and peer patterns
- least privilege by default
- Intelligent request intake free text to structured entitlements with missinginfo prompts
- Automated SoDpolicy prechecks and exception workflows
- Approval routing optimisation and onboarding copilot for service deskIAM ops
- Define confidence thresholds and humanintheloop decision points
- Data integration operating model
- Coordinate data sourcing and quality across HR feeds
- IAM catalogue historical requests org hierarchy and ticketingworkflow tools
- Partner with engineering to integrate into IAM workflows eg ServiceNowIGA tooling
- ensuring secure APIs logging and resiliency
- Define BAU support model runbooks and training for IAM ops and approvers
- Risk controls
- Responsible AI
- Ensure alignment with privacy information security and model risk management expectations
- Drive auditability decision rationale approvals model outputs and change history
- Implement guardrails for GenAI where used
- data leakage prevention
- prompt controls
- content filtering
- monitoring
- Define monitoring for model performance and control effectiveness
- drift override rates
- exception volumes
- Value realisation
- Define and track KPIs onboarding cycle time rework rate access errors SoD conflicts prevented approver turnaround time
- Drive adoption through stakeholder engagement communications and continuous improvement
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